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Sebastian Perez Saaibi
I’ve built and led Data Science and Machine Learning teams for the past 8 years, and have over a decade of experience using Data Science and Applied Machine Learning to solve real-world business problems in industries such as Commerce, Healthcare, and Finance. I’ve had the opportunity to be an individual contributor, startup founder and technical manager throughout this journey.
I’m interested in building teams of Data Scientists, Machine Learning Engineers and Data Engineers to come up with products that solve complex organizational challenges, as well as mentoring data scientists and technical managers.
I like good coffee, spending time with my family, running, and reading.
Current Position
Sr. Manager Data Science and Engineering
Shopify
Ottawa, Canada
Current - 2020
- Lead the Data Science and Engineering teams in charge of Insights. We build tools, models and data products that enable data-informed decisions for merchants. Our goal is to use Data Science and Machine Learning to make commerce better for everyone, everywhere.
Education
MSc. Computational Science and Engineering (GPA: 5.1/6.0)
ETH Zürich
Zürich, Switzerland
2010 - 2008
- Master’s Thesis: Dynamic Risk Diversification in Portfolio Optimization. Advisor: PD. Dr. Diethelm Würtz
- Semester Thesis: Success & Failure in Open Source Software Distributions. Advisor: Prof. Dr. Didier Sornette
BSc. Physics; BSc. Mechanical Engineering (GPA: 4.4/5.0)
Universidad de los Andes
Bogotá, Colombia
2008 - 2003
- Physics Thesis: Random Matrix Theory Application to Portfolio Optimization on the IGBC. Advisor: Prof. Dr. Gabriel Tellez Acosta.
- Mechanical Engineering Thesis: Microscopic Modeling of two-particle Sintering. Advisor: Prof. Dr. Jairo A. Escobar.
High School Diploma, Honors
La Quinta del Puente Highscool
Bucaramanga, Colombia
2002 - 1992
- Original Degree: Bachiller Académico con énfasis en Ciencias & Multimedia
Industry Experience
I’m a Data Scientist and technologist focused on building global data products using Data Science and Machine Learning. I brew data.
Director of Data Science
Phreesia
New York City, NY
2020 - 2018
- Build Phreesia’s Data Science and Machine Learning team, inside the Life Sciences organization. Create and lead the strategy and vision.
- Attract, hire, mentor and grow a team of Machine Learning Engineers, Data Scientists and Data Engineers (10+). Provide thought leadership to internal and external business executives. Hands-on data product building, algorithmic selection, model validation and evaluation of Phreesia’s ML production services.
- Set an open, collaborative, educational, hands-on team culture that works cross-functionally with other business units. Build and promote the data science competencies and growth framework
Head of Machine Learning and Data Science
Pager
New York City, NY
2018 - 2015
- Lead Pager’s ML strategy and vision by building and managing a team of Data Scientists and Engineers, guiding patients to better care one model at a time. Hands-on implementations, algorithmic selection, model validation, training, testing and statistical validity of data products.
- Predictive Analytics and Reporting: Build end-to-end ETL systems for data extraction, wrangling, processing and modeling. Designed Pager’s OKRs and automated Internal and External Reports (interactive dashboards, board presentations)
- Machine Learning: Productionize ML-based APIs for Pager’s care navigation platform.
CEO and Co-Founder, Chief Data Scientist
Aentropico
Rio de Janeiro, Brazil
2014 - 2012
- Aentropico is Latin America’s first Predictive Analytics startup. We built a self-service dashboard that helped small and medium retailers transform their data into useful and practical insights to facilitate decision making.
Quantitative Analyst: Trading Strategies R&D
Macx Red AG
Zug, Switzerland
2011 - 2010
- Founding member of Macxred’s research team for Quantitative, High-Frequency Trading Systems.
- Design, testing and implementation of portfolio-based risk mitigation schemes. Promote the design of an automated strategy selection mechanism.
- Implement robust asset allocation and Regime-based Trend Following strategies.
Maintenance Engineer
BHP Billiton - Spence
Antofagasta, Chile
2008
- Mine Maintenance. BHP Billiton’s Graduate Program. Statistical Analyses to reduce the time between component failure (MTBF). Close monitoring of the electro-mechanical condition of the entire Caterpillar heavy-duty fleet.
Research Experience
E.J. Safra Network Fellow
Harvard University
Cambridge, MA
2015 - 2012
- Winner of the “System to Monitor Institutional Corruption” Innocentive Challenge. Built a Complex network model to monitor corruption in Colombia’s largest corporations. Identified revolving doors between corporations and government officials. Contributed to data science events such as the “iCorruption Hackathon 2015”.
Visiting Research Assistant
University of Maryland
College Park, MD
2006
- Laboratory for Microtechnologies. Project Director: Prof. Dr. Elisabeth Smela. Research Project: Cost reduction and characterization of Compliant Electrodes.
Teaching Experience
Assistant Professor
Universidad de los Andes
Bogotá, Colombia
2015
- Wrote syllabus and taught ‘Computational Tools’. Basic introduction to computational tools for physicists, mathematicians and geoscientists. See repo
- Wrote syllabus and taught ‘Computational Methods’: Intro to the most common and useful Computational Methods for physicists, mathematicians and geoscientists. See repo
Teaching and Grading Assistant
Universidad de los Andes
Bogotá, Colombia
2007 - 2004
- Grading Assistant: Classical Mechanics, Modern Physics and Electromagnetism.
- Teaching Assistant: Heat Transfer, Classical, Thermal & Fluid Dynamics.
- Research Assistant: Material Characterization and Fracture Mechanics.
Selected Data Science Writing
Selected Publications, Posters, and Talks
What’s a Data Scientist? A look inside its toolbox
Science Hack Day
Bogotá, Colombia
2015
R Generator Tool for Google Motion Charts
Uniandes Physics Colloquim
Bogotá, Colombia
2010
Diving into Econophysics using R
Rmetrics Summer School in Computational Finance
Basel, Switzerland
2010